The expected power of genome-wide linkage disequilibrium testing using single nucleotide polymorphism markers for detecting a low-frequency disease variant.

Abstract:

:The expected power of genome-wide linkage disequilibrium (LD) testing for a low-frequency disease variant was examined using a simple genetic model in which the degree of LD between the disease variant and the adjacent single nucleotide polymorphism (SNP) marker decreases in proportion to the number of generations since the LD-generating event. In this study, the frequency of the SNP marker being in complete LD with a low-frequency disease variant at the LD-generating event was regarded as the random variable having the probability distribution expected from the neutral infinite sites model, which enables us to derive the formula for calculating the expected power of genome-wide LD testing without determining the allele frequency of the associated SNP marker. Such a treatment is essential for the evaluation of the power of LD testing, because the frequency of the associated marker allele is always unknown. The main results obtained are as follows: (1) genome-wide LD testing with a case-control design could identify a disease variant with a high penetrance, while a low-frequency disease variant showing a low penetrance is difficult to detect; (2) although the degree of LD increases as the number of markers increases, the power of LD testing does not necessarily increase after the significance level is adjusted by the Sidák correction or the Bonferroni correction based on the number of testings; (3) the use of SNP markers with only high-frequency minor alleles is more powerful for detecting LD even with a low-frequency disease variant than the use of SNP markers with both high- and low-frequency minor alleles. Thus, the study design of LD testing must be evaluated prior to the investigation. The present study will provide a guideline for determining the number of SNP markers and the range of SNP allele frequencies suitable for genome-wide LD testing.

journal_name

Ann Hum Genet

journal_title

Annals of human genetics

authors

Ohashi J,Tokunaga K

doi

10.1017/S0003480002001197

subject

Has Abstract

pub_date

2002-07-01 00:00:00

pages

297-306

issue

Pt 4

eissn

0003-4800

issn

1469-1809

pii

S0003480002001197

journal_volume

66

pub_type

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